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Record W4220847597 · doi:10.1016/j.crgsc.2022.100302

Co-transport of PFCs in the environment- An interactive story

2022· article· en· W4220847597 on OpenAlexafffund
Pratishtha Khurana, Noha Hasaneen, Rama Pulicharla, Guneet Kaur, Satinder Kaur Brar

Bibliographic record

VenueCurrent Research in Green and Sustainable Chemistry · 2022
Typearticle
Languageen
FieldEnvironmental Science
TopicPer- and polyfluoroalkyl substances research
Canadian institutionsYork University
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsEnvironmental chemistryContaminationBioaccumulationEnvironmental scienceChemistryBiochemical engineeringEcologyBiologyEngineering

Abstract

fetched live from OpenAlex

The fate and transport of perfluorinated compounds (PFCs) have been extensively studied and widely reviewed recently. Literature reports that they are persistent and may travel considerable distances in all environmental compartments, such as water, sediment, air, and soil owing to their chemical and thermal stability. However, their transport with co-existing contaminants and their potential as vectors for various chemical and biological contaminants has been overlooked. In this sense, the present note addresses the role of PFCs as vectors, making this review one of its kind. This graphical review discusses the ability of PFCs to interact with different matrices, such as heavy metals, organic matter, and bacterial cell membranes via electrostatic and hydrophobic interactions, and aggregation and micelle formation, allowing them to act as vectors for various chemical and biological contaminants. This PFC-mediated transport can alter the tendency of both -PFCs and the contaminant to persist, bioaccumulate, and co-transport between and within disparate environmental matrices, as well as their interfaces. Further, this joint toxicity could potentially have elevated eco-toxicological impacts, including altered cell membrane permeability and increased cell uptake, which still need to be explored, thereby demonstrating the need for future investigations in this regard.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.004
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.602
Threshold uncertainty score0.998

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0040.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0030.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.042
GPT teacher head0.356
Teacher spread0.315 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

Study designObservational
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations7
Published2022
Admission routes2
Has abstractyes

Explore more

Same venueCurrent Research in Green and Sustainable ChemistrySame topicPer- and polyfluoroalkyl substances researchFrench-language works237,207